用绿岸望远镜在1.15-1.73 GHz对开普勒场中TRAPPIST-1、LHS 1140和10个行星系的技术特征的搜索
A search for technosignatures from TRAPPIST-1, LHS 1140, and 10 planetary systems in the Kepler field with the Green Bank Telescope at 1.15-1.73 GHz
摘要：
作为我们正在进行的技术签名搜索的一部分，我们在2017年5月用100米直径的绿岸望远镜的L波段接收器（1.15-1.73 GHz）收集了超过3 TB的数据。这些观测主要集中在开普勒领域的行星系，但也包括最近发现的TRAPPIST-1和LHS 1140系统的扫描。我们使用与Margot等人（2018）描述的技术大致相似的技术在该数据集中搜索窄带信号的结果。我们改进的数据处理管道将$\sim$ 600万个检测到的信号中的超过$98\%$分类为人为射频干扰（RFI）。在其余的候选者中，有30个是在RFI密集的频率区域之外检测到的。这些候选人经过仔细检查，确定为陆地起源。我们讨论了与忽略频率空间周围的无线电technosignature检测管道的候选检测的常见做法相关的问题。这些问题包括对优值的估计不准确，以及对技术签名普及率的上限不可靠。我们提出了一种算法，减轻这些问题，提高了搜索的效率。具体来说，与Margot et al.（2018）相比，我们的新算法将候选检测的数量增加了四倍以上。
英文摘要：
As part of our ongoing search for technosignatures, we collected over three terabytes of data in May 2017 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused primarily on planetary systems in the Kepler field, but also included scans of the recently discovered TRAPPIST-1 and LHS 1140 systems. We present the results of our search for narrowband signals in this data set with techniques that are generally similar to those described by Margot et al. (2018). Our improved data processing pipeline classified over $98\%$ of the $\sim$ 6 million detected signals as anthropogenic Radio Frequency Interference (RFI). Of the remaining candidates, 30 were detected outside of densely populated frequency regions attributable to RFI. These candidates were carefully examined and determined to be of terrestrial origin. We discuss the problems associated with the common practice of ignoring frequency space around candidate detections in radio technosignature detection pipelines. These problems include inaccurate estimates of figures of merit and unreliable upper limits on the prevalence of technosignatures. We present an algorithm that mitigates these problems and improves the efficiency of the search. Specifically, our new algorithm increases the number of candidate detections by a factor of more than four compared to Margot et al. (2018).
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